Bitte verwenden Sie diesen Link, um diese Publikation zu zitieren, oder auf sie als Internetquelle zu verweisen: https://hdl.handle.net/10419/246746 
Autor:innen: 
Erscheinungsjahr: 
2021
Schriftenreihe/Nr.: 
Working Paper No. 021.2021
Verlag: 
Fondazione Eni Enrico Mattei (FEEM), Milano
Zusammenfassung: 
The analysis and measurement of poverty is a crucial and unsolved issue in the field of social science. This work aims to measure poverty as a multidimensional notion using a new composite indicator. However, subjective choices as different weighting schemes on the indicator's construction could affect their interpretation and policy. It is necessary to consider the possible weighting configurations randomly to overcome this problem, and it is proposed in this work as interval-based composite indicators based on the results. This work aims to obtain robust and reliable measures based on a relevant conceptual model of poverty we have identified, considering various factors as weightings. Methodologically speaking, it is proposed an original procedure for measuring poverty in which it is computed a different composite indicator for each simulated weighting scheme of the identified factors. The weighting scheme in the Monte-Carlo simulation randomly creates an interval-based composite indicator based on the results. The different intervals are compared using different criteria (upper bound, center, and lower bound), and various rankings help analyze extreme scenarios and policy hypotheses. Critical situations are identified in Sicilia, Calabria, Campania and Puglia. The results demonstrate a relevant and consistent indicator measurement and the shadow sector's relevant impact on the final measures.
Schlagwörter: 
Poverty
Composite Indicators
Interval Data
Interval-based Composite Indicators
Symbolic Data
JEL: 
C02
C15
C43
I3
I32
Dokumentart: 
Working Paper

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